Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Florian Heimerl"'
Publikováno v:
PacificVis
Magic lens based focus+context techniques are powerful means for exploring document spatializations. Typically, they only offer additional summarized or abstracted views on focused documents. As a consequence, users might miss important information t
Autor:
Alex Endert, Shah Rukh Humayoun, Michael Gleicher, Florian Heimerl, Shenyu Xu, Remco Chang, Dylan Cashman, Cong Liu, Subhajit Das
Most visual analytics systems assume that all foraging for data happens before the analytics process; once analysis begins, the set of data attributes considered is fixed. Such separation of data construction from analysis precludes iteration that ca
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b445d3b2b573d0ae0757c57a56b7f919
http://arxiv.org/abs/2009.02865
http://arxiv.org/abs/2009.02865
Machine learning practitioners often compare the results of different classifiers to help select, diagnose and tune models. We present Boxer, a system to enable such comparison. Our system facilitates interactive exploration of the experimental resul
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::44e5a265c902e18869368c8d90957838
Autor:
Florian Heimerl, Michael Gleicher
Publikováno v:
Computer Graphics Forum. 37:253-265
Publikováno v:
IEEE Transactions on Multimedia. 18:2149-2160
The analysis of inherent structures of movies plays an important role in studying stylistic devices and specific, content-related questions. Examples are the analysis of personal constellations in movie scenes, dialogue-based content analysis, or the
Publikováno v:
HICSS
This paper introduces embComp, a novel approach for comparing two embeddings that capture the similarity between objects, such as word and document embeddings. We survey scenarios where comparing these embedding spaces is useful. From those scenarios
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3930b608bf1758bc319328c6dc231980
Publikováno v:
VISIGRAPP (3: IVAPP)
Autor:
Abigail Mosca, Kendall Park, Subhajit Das, Shah Rukh Humayoun, John Thompson, Florian Heimerl, Michael Gleicher, John Stasko, Bahador Saket, Remco Chang, Alex Endert, Dylan Cashman
Many visual analytics systems allow users to interact with machine learning models towards the goals of data exploration and insight generation on a given dataset. However, in some situations, insights may be less important than the production of an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e7029c367c16b97a8890600c7a036724
Publikováno v:
BDVA
Personal networks formed within scientific communities and the collaborations they yield are one of the driving forces behind innovation and new discoveries. Luckily, successful collaboration produces analyzable data points in the form of publication